Search for dissertations about: "machine foundation"
Showing result 1 - 5 of 62 swedish dissertations containing the words machine foundation.
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1. Energy Efficient Machine-Type Communications over Cellular Networks : A Battery Lifetime-Aware Cellular Network Design Framework
Abstract : Internet of Things (IoT) refers to the interconnection of uniquely identifiable smart devices which enables them to participate more actively in everyday life. Among large-scale applications, machine-type communications (MTC) supported by cellular networks will be one of the most important enablers for the success of IoT. READ MORE
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2. Failure diagnostics using support vector machine
Abstract : Failure diagnostics is an important part of condition monitoring aiming to identify incipient failures in early stages. Accurate and efficient failure diagnostics can guarantee that the operator makes the correct maintenance decision, thereby reducing the maintenance costs and improving system availability. READ MORE
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3. Simulating Group Interactions through Machine Learning and Human Perception
Abstract : Human-Robot/Agent Interaction is well researched in many areas, but approaches commonly either focus on dyadic interactions or crowd simulations. However, the intermediate structure between individuals and crowds, i.e., small groups, has been studied less. READ MORE
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4. Predictive Techniques and Methods for Decision Support in Situations with Poor Data Quality
Abstract : Today, decision support systems based on predictive modeling are becoming more common, since organizations often collect more data than decision makers can handle manually. Predictive models are used to find potentially valuable patterns in the data, or to predict the outcome of some event. READ MORE
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5. Utilizing Diversity and Performance Measures for Ensemble Creation
Abstract : An ensemble is a composite model, aggregating multiple base models into one predictive model. An ensemble prediction, consequently, is a function of all included base models. Both theory and a wealth of empirical studies have established that ensembles are generally more accurate than single predictive models. READ MORE